State-dependent activity dynamics of hypothalamic stress effector neurons

Abstract

The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to an elevated emergency response. However, the neural mechanisms underlying this state-dependent change remain largely unknown. Using a combination of in vivo and ex vivo electrophysiology with computational modeling, we report that corticotropin releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN), the effector neurons of hormonal stress response, rapidly transition between distinct activity states through recurrent inhibition. Specifically, in vivo optrode recording shows that under non-stress conditions, CRH_PVN neurons often fire with rhythmic brief bursts (RB), which, somewhat counterintuitively, constrains firing rate due to long (~2 s) interburst intervals. Stressful stimuli rapidly switch RB to continuous single spiking (SS), permitting a large increase in firing rate. A spiking network model shows that recurrent inhibition can control this activity-state switch, and more broadly the gain of spiking responses to excitatory inputs. In biological CRH_PVN neurons ex vivo, the injection of whole-cell currents derived from our computational model recreates the in vivo-like switch between RB and SS, providing direct evidence that physiologically relevant network inputs enable state-dependent computation in single neurons. Together, we present a novel mechanism for state-dependent activity dynamics in CRH_PVN neurons.

Keywords: CRH; burst firing; hypothalamus; mouse; neuroendocrine; neuroscience; recurrent circuit; stress.

Figure 1.. Optogenetic identification of CRH_PVN neuron single-unit.

(A) Electrode tract (purple), TdTomato-expressing CRH_PVN neurons (red) and ChR2-EYFP (green) expression. (B) An example for an isolated single-unit (blue) that also responded to light (cyan). (C) Raster plot (top) and peristimulus time histogram (PSTH, bottom) in response to 5 ms blue light from a representative unit. (D) A summary graph for the probability of firing before (−20–0 ms) and after blue light illumination (0–20 ms). Light-responsive units in black (n=18) and non-responsive units in gray (n=18). (E) Raster plot (top) and PSTH (bottom) for a representative single-unit responding to 50 ms blue light. (F) Summary of firing rate time course following 5 ms (tick) and 50 ms (open circle) blue light. n=18. SD is represented as error bars.

Figure 2.. CRH_PVN neurons fire in rhythmic bursts and single spikes.

(A) Two distinct spike patterns in a representative single-unit (top: single spikes; bottom: bursts indicated by arrow). (B) Interspike interval (ISI) distribution for the representative single-unit shown in A. (C) A summary plot for burst rates among CRH_PVN neurons during non-stress baseline recordings. The criterion for burst firing neurons (purple) was set as 0.1 burst/s. A horizontal bar indicates the average. (D) A summary graph for burst length distribution (n=10). (E) Summary interburst interval (IBI) distribution (n=10). Standard deviation is represented in the graphs as the error bars (D) and dotted line (E).

Figure 2—figure supplement 1.. Interspike interval (ISI) histograms for all CRH_PVN units.

Burst rate (BR) is indicated on the top-right corner of individual histograms. Unit 18 and 30 did not fire bursts and are shown in gray.

Figure 3.. CRH_PVN neurons are constrained to low activity during rhythmic bursting.

(A) Peristimulus time histogram (PSTH) for a representative single-unit responding to sciatic nerve stimulation (1.5 mA, 0.5 ms × 5 pulses at 20 Hz, red line). (B–D) Raster plots for the unit shown in A for all spikes (B), bursts (C) and single spikes (SS) (D). (E, F) Summary time course for bursts (E) and SS (F). n=13. (G–I) Summary changes in all spikes (G, paired t-test, n=13, p=0.0108), bursts (H, paired t-test, n=13, p=0.0167) and SS (I, paired t-test, n=13, p=0.0025) before (baseline, BL) and after sciatic nerve stimulation (NS). (J, K) Time course of firing rate (J) and interspike interval (ISI) (K) for a representative single-unit during baseline recording. Gray lines are the running average (30 s) of firing rate. (L) The relationship between burst rate and total firing rate for the representative single-unit shown in J and K. For each time bin (10 s), total spike rate was plotted against burst rate. (M) Pooled data for all units (n=18).

Figure 3—figure supplement 1.. Firing pattern changes persist longer with higher intensity nerve stimulations.

Raster plots of a representative single unit responding to different intensities of sciatic nerve stimulations. (A–C) 0.5 mA, (D–F) 1.0 mA, (G–I) 1.5 mA, and (J–L) 2.0 mA. Raster plots for all spikes (A, D, G, J), burst firing (B, E, H, K) and single spikes (C, F, I, L). Note that the highest intensity stimulation (2.0 mA) caused persistent decrease of burst firing and increase of single spiking across trial durations compared to lower intensity (0.5–1.5 mA) stimulations.

Figure 4.. Prolonged silent periods precede burst firing.

(A) Preceding and proceeding interspike interval (ISI) plotted for individual spikes recorded from a representative single-unit. Blue rectangle indicates spikes with proceeding ISI <6 ms. Red rectangle indicates spikes with preceding ISI <20 ms. Left. An example of a burst episode. (B) Summary of probability of burst firing relative to preceding silence (ISI). (C) Summary of probability of burst firing relative to proceeding silence (ISI). (D) Mean preceding silence as a function of event length. One-way ANOVA, p<0.0001; Tukey’s multiple comparisons test, single vs 2 (p<0.0001), 3 (p=0.0001), ≥ 4 (p=0.0004) (E) Mean proceeding silence as a function of event length. One-way ANOVA, p=0.0131; Tukey’s multiple comparisons test, single vs 2 (p=0.0573), 3 (p=0.0437), ≥ 4 (p=0.2885) SD is represented in the graphs as dotted lines (B, C) and the error bars (D, E).

Figure 5.. Recurrent inhibitory circuits generate burst firing and gate firing response to excitatory inputs in CRH_PVN neurons.

(A) CRH model neuron in silico (black) fitted to current-clamp recordings of CRH_PVN neurons ex vivo (red). (B) F-I curves for in silico (black) and ex vivo (red) neurons. (C) Network model diagram. (D) Time course of interspike interval (ISI) for a representative model CRH neuron. Gray line is the running average firing rate. (E) Summary burst length distribution for model simulations (n=283 for burst rate >0.1 Hz). (F) Summary IBI distribution for model simulations (n=283 for burst rate >0.1 Hz). (G) An example ISI time course before and after a drop of GABA release (Pr 0.8 → 0.1) from 200 s. Gray line is the running average firing rate. (H–J) Summary changes in all spikes (H, paired t-test, p<0.0001, n=500), bursts (I, paired t-test, p<0.0001, n=500) and single spikes (SS) (J, paired t-test, p<0.0001, n=500) before (BL) and after the GABA release drop. (K) An example ISI time course before and after a drop of GABA release (Pr 0.8 → 0.1) combined with an increase in spike-triggered adaptation current from 200 s. Gray line is the running average firing rate. (L–N) Summary changes in all spikes (L, paired t-test, p<0.0001, n=500), bursts (M, paired t-test, p<0.0001, n=500) and SS (N, paired t-test, p<0.0001, n=500) before (BL) and after combined removal of GABA release and increased spike-triggered adaptation current. (O) An example ISI time course before and after EPSP frequency increase (30 Hz → 60 Hz) from 200 s. Gray line is the running average firing rate. (P) An example ISI time course before and after the combined change in GABA release and spike-triggered adaptation current, followed by an increase in EPSP frequency (30 Hz → 60 Hz) from 400 s. (Q) Summary graph for changes in firing rate before (30 Hz) and after EPSP frequency increase (60 Hz) with (white) and without recurrent inhibition (pink). Two-way ANOVA (EPSP × Recurrent inhibition interaction, p<0.0001; Tukey’s multiple comparisons test, BL-30 Hz 2.942 ± 2.220 Hz vs BL-60 Hz 3.895 ± 3.252 Hz, p<0.0001; ↓GABA+↑Ad. Curr.-30 Hz 7.548 ± 2.068 Hz vs ↓GABA+↑Ad. Curr.-60 Hz 10.630 ± 3.387 Hz, p<0.0001). SD is represented in the graphs as the error bars.

Figure 5—figure supplement 1.. The temporal relationship between network and intrinsic properties with burst firing.

(A) Overlay of simulated membrane voltage (Vm; red) of representative traces of burst firing from model neurons (n_neurons = 5; n_bursts = 10). Note that spikes are truncated to 0 mV in this example. (B) The incoming excitatory conductance (Ge; green). (C) The incoming inhibitory conductance (Gi; blue). (D) The spike-triggered adaptation (w; pink). (E) The representative current (I total; black) that each neuron receives. The representative current is the proportional sum of the above network and intrinsic inputs (Ge, Gi, and w). Representative traces were selected based on an initial interspike interval lower than 6 ms and a preceding interburst interval (IBI) of 200–220 ms. Traces are aligned to the second burst.

Figure 6.. Recurrent inhibitory circuits underlie burst firing.

(A) Diagram of ‘network clamp’ experiment. (B–D) Time course of interspike interval (ISI) for a representative model CRH neurons (B), a biological CRH_PVN neuron injected with network current (C) and overlay (D). (E) Correlation coefficient between the time series of model neuron spike train in silico, a biological CRH_PVN neurons’ spike train ex vivo, and a shuffled spike train consisting of the model spike train with ISI’s shuffled (n=5). (F, G) Spike firing patterns in response to network current (F) and depolarizing current step (G) in a biological CRH_PVN neuron. (H) ISI distribution of spikes generated by network current (red) and steps of current (purple). Note that spikes with ISI smaller than 30 ms were used for comparison. (I, J) Network currents of variable length (I) and corresponding membrane voltage changes in CRH_PVN neurons (J). (K) Summary graph for the shortest ISI triggered by network currents of variable lengths. SD is represented in the graph as the error bars. (L) CRH_PVN neuron’s firing response to network current with (blue) and without tetrodotoxin (TTX, 1 µM, red). (M) Firing of CRH_PVN neuron (orange) and magnocellular neuron (brown) in response to an identical network current (black). (N) Summary of ISI triggered by network current in CRH_PVN and magnocellular neurons. (O–Q) A representative ISI time course for the transition between rhythmic burst and single spiking in a model CRH neuron (O), a biological CRH_PVN neuron injected with the network current of the model neuron shown in O, and overlay (Q).